المؤلفون: Andrea Murari, Michele Lungaroni, Riccardo Rossi, Luca Spolladore, Michela Gelfusa

المصدر: Complexity, Vol 2022 (2022)

مصطلحات موضوعية: Electronic computers. Computer science, QA75.5-76.95

وصف الملف: electronic resource

العلاقة: https://doaj.org/toc/1099-0526Test

الوصول الحر: https://doaj.org/article/abfa40fb800e47e88e9709101e145c98Test

المؤلفون: Michele Lungaroni, Andrea Murari, Emmanuele Peluso, Pasqualino Gaudio, Michela Gelfusa

المصدر: Complexity, Vol 2019 (2019)

مصطلحات موضوعية: Electronic computers. Computer science, QA75.5-76.95

وصف الملف: electronic resource

العلاقة: https://doaj.org/toc/1076-2787Test; https://doaj.org/toc/1099-0526Test

الوصول الحر: https://doaj.org/article/ffc8644b8a264af684aa6b7cb4c99830Test

المؤلفون: Andrea Murari, Emmanuele Peluso, Michele Lungaroni, Riccardo Rossi, Michela Gelfusa, JET Contributors

المصدر: Applied Sciences, Vol 10, Iss 19, p 6683 (2020)

مصطلحات موضوعية: disruptions, prediction, support vector machines, classification and regression trees (CART), ensemble of classifiers, symbolic regression, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999

وصف الملف: electronic resource

العلاقة: https://www.mdpi.com/2076-3417/10/19/6683Test; https://doaj.org/toc/2076-3417Test

الوصول الحر: https://doaj.org/article/e292b52356774145babaf4fce7186c70Test

المؤلفون: Andrea Murari, Riccardo Rossi, Michele Lungaroni, Pasquale Gaudio, Michela Gelfusa

المصدر: Entropy, Vol 22, Iss 2, p 141 (2020)

مصطلحات موضوعية: machine learning tools, information theory, information quality ratio, total correlations, encoders, autoencoders, Science, Astrophysics, QB460-466, Physics, QC1-999

وصف الملف: electronic resource

العلاقة: https://www.mdpi.com/1099-4300/22/2/141Test; https://doaj.org/toc/1099-4300Test

الوصول الحر: https://doaj.org/article/0bdf7c6aeee14da187001275346f38cfTest

المؤلفون: Andrea Murari, Emmanuele Peluso, Francesco Cianfrani, Pasquale Gaudio, Michele Lungaroni

المصدر: Entropy, Vol 21, Iss 4, p 394 (2019)

مصطلحات موضوعية: Model Selection Criteria, Bayesian Information Criterion (BIC), Akaike Information Criterion (AIC), Shannon Entropy, Geodesic Distance, Science, Astrophysics, QB460-466, Physics, QC1-999

وصف الملف: electronic resource

العلاقة: https://www.mdpi.com/1099-4300/21/4/394Test; https://doaj.org/toc/1099-4300Test

الوصول الحر: https://doaj.org/article/5043cabb1da24d8e92019fb0afd427f2Test

المؤلفون: Andrea Murari, Michele Lungaroni, Emmanuele Peluso, Pasquale Gaudio, Ernesto Lerche, Luca Garzotti, Michela Gelfusa, JET Contributors

المصدر: Entropy, Vol 20, Iss 9, p 627 (2018)

مصطلحات موضوعية: transfer entropy, mutual information, Pearson correlation coefficient, time series, causality detection, sawteeth, pacing, ELMs, pellets, Science, Astrophysics, QB460-466, Physics, QC1-999

وصف الملف: electronic resource

العلاقة: http://www.mdpi.com/1099-4300/20/9/627Test; https://doaj.org/toc/1099-4300Test

الوصول الحر: https://doaj.org/article/0043bc74062d483ca46eb8153943b59dTest

المؤلفون: Andrea Murari, Riccardo Rossi, Michele Lungaroni, Pasquale Gaudio, Michela Gelfusa

المصدر: Proceedings; Volume 46; Issue 1; Pages: 19

مصطلحات موضوعية: Machine Learning Tools, Information Theory, Information Quality Ratio, Total Correlations, Encoders, Autoencoders

وصف الملف: application/pdf

العلاقة: https://dx.doi.org/10.3390/ecea-5-06666Test

الإتاحة: https://doi.org/10.3390/ecea-5-06666Test

المؤلفون: Andrea Murari, Riccardo Rossi, Luca Spolladore, Michele Lungaroni, Pasquale Gaudio, Michela Gelfusa

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::797974fd0676ed0b61bdf2781b058475Test
https://doi.org/10.21203/rs.3.rs-2449577/v1Test

المؤلفون: Andrea Murari, Riccardo Rossi, Michele Lungaroni, Matteo Baruzzo, Michela Gelfusa

المساهمون: Murari, A, Rossi, R, Lungaroni, M, Baruzzo, M, Gelfusa, M

مصطلحات موضوعية: disruptions, machine learning predictors, adaptive learning, ensembles of classifiers, transfer learning, de-learning, trajectory learning, stacks of predictors, Settore ING-IND/18 - FISICA DEI REATTORI NUCLEARI

العلاقة: info:eu-repo/semantics/altIdentifier/wos/WOS:000619787700001; volume:61; issue:3; journal:NUCLEAR FUSION; https://hdl.handle.net/2108/311065Test; info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85102169355

الإتاحة: https://doi.org/10.1088/1741-4326/abc9f3Test
https://hdl.handle.net/2108/311065Test

المؤلفون: Stefan Matejcik, Francesco Romanelli, Augusto Pereira González, Jesús Vega, Bohdan Bieg, Emmanuele Peluso, Vladislav Plyusnin, José Vicente, Alberto Loarte, Michele Lungaroni, Bor Kos, Andrea Murari, Axel Jardin, Rajnikant Makwana, CHIARA MARCHETTO, Choong-Seock Chang, Manuel Garcia-munoz

المساهمون: Department of Physics, Materials Physics

المصدر: Fusion engineering and design 130 (2018): 62–68. doi:10.1016/j.fusengdes.2018.02.087
info:cnr-pdr/source/autori:Lungaroni M.; Murari A.; Peluso E.; Vega J.; Farias G.; Gelfusa M./titolo:On the potential of ruled-based machine learning for disruption prediction on JET/doi:10.1016%2Fj.fusengdes.2018.02.087/rivista:Fusion engineering and design/anno:2018/pagina_da:62/pagina_a:68/intervallo_pagine:62–68/volume:130
Fusion Engineering and Design

مصطلحات موضوعية: Boosting (machine learning), Computer science, education, Machine learning, computer.software_genre, 114 Physical sciences, 01 natural sciences, Boosting, 010305 fluids & plasmas, Noise-based ensembles, Bagging, 0103 physical sciences, Classification and regression trees, General Materials Science, 010306 general physics, Civil and Structural Engineering, business.industry, Mechanical Engineering, Settore ING-IND/18 - Fisica dei Reattori Nucleari, Random forests, Random forest, Disruptions, Nuclear Energy and Engineering, Machine learning predictors, Artificial intelligence, business, computer

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e671b380cb805703aa38f025c056bd86Test
https://doi.org/10.1016/j.fusengdes.2018.02.087Test